{"id":56,"date":"2015-06-16T13:44:07","date_gmt":"2015-06-16T11:44:07","guid":{"rendered":"http:\/\/members.loria.fr\/thierrygartiser\/?page_id=56"},"modified":"2025-09-17T19:12:50","modified_gmt":"2025-09-17T17:12:50","slug":"accueil","status":"publish","type":"page","link":"https:\/\/members.loria.fr\/SAridhi\/","title":{"rendered":"Home"},"content":{"rendered":"

I am an Associate Professor (Ma\u00eetre de conf\u00e9rences), HDR of Computer Science at TELECOM Nancy<\/strong><\/a> at the University of Lorraine<\/strong><\/a>.\u00a0 I am member of MOSAIK<\/a> research team (Inria – CNRS) at the Lorraine Laboratory of Research in Computer Science and its Applications<\/span><\/strong> (LORIA)<\/a>. Previously, I served as a Visiting Researcher at the Montreal Institute for Learning Algorithms (Mila)<\/strong><\/a> in Montreal, Canada. I also worked as a postdoctoral researcher at Aalto University<\/strong> in Finland and as a research fellow at the University of Trento<\/strong> in Italy. I received my Ph.D. in Computer Science from the Blaise Pascal University<\/strong>, France in 2013 and my\u00a0 Habilitation to Conduct Research (HDR) from the University of Lorraine<\/b>, France in 2023. My research interests include Big Data Management and Analytics, Data Mining, machine learning and Bioinformatics.<\/p>\n

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News!<\/span><\/h2>\n

March 2026<\/strong> Invited talk<\/strong> on Modeling Biomedical Dynamics: Link Prediction in Temporal Knowledge Graphs for Drug Repurposing<\/em>. Journ\u00e9e DoMeST \u00ab\u00a0Analyse et Gestion des Donn\u00e9es M\u00e9dicales Spatio-Temporelles (DoMeST)<\/a>\u00ab\u00a0<\/p>\n

Febrary 2026<\/strong>\u00a0 Ph.D. Thesis on <\/strong>Assessing Crohn\u2019s Disease Severity Using Multimodal AI. (If intresseted, please send contact me: sabeur.aridhi@loria.fr)\u00a0<\/em><\/p>\n

Jan 2025<\/strong>\u00a0 M2 internship offer<\/span> on\u00a0<\/strong>Multimodal Machine Learning in Healthcare: Application to Crohn’s Disease<\/i> [PDF<\/a>]<\/strong><\/p>\n

December 2024<\/b> Our paper Knowledge graph representation learning: a comprehensive and experimental overview <\/b> has been accepted for publication in Computer Science Review<\/a> (IF = 13.3<\/strong>)<\/em><\/span>.<\/p>\n

December 2024<\/b> We are editing a special issue of Supercomputing journal<\/a> on Scalable and Deep Graph Learning and Mining <\/b>. Please submit your paper here<\/a>
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October 2024<\/b> Our paper Empirical Analysis of Knowledge Graph Representation Learning Techniques <\/b> has been accepted at the 13th International Conference on Complex Networks and their Applications, COMPLEX NETWORKS 2024, Istanbul, Turkey<\/p>\n

August 2024<\/strong> I am giving a talk on \u00ab\u00a0Knowledge graph embedding and link prediction for explainable drug repurposing<\/span><\/span>\u00a0\u00bb at the Meharry School of Applied Computational Sciences<\/a>, Nashville, TN, USA<\/span><\/span><\/em><\/p>\n

July 2024<\/strong> I am giving a talk on \u00ab\u00a0Ensemble knowledge graph embedding and link prediction for drug repurposing\u00a0\u00bb in the Healthcare & AI reading group at <\/em>Mila<\/a>, Montreal, QC, Canada
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July 2024<\/strong> I am visiting the Montreal Institute for Learning Algorithms (Mila)<\/a> in Montreal, QC, Canada
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May 2024<\/strong> Our workshop proposal \u00ab\u00a0International workshop on Scalable and Deep Graph Learning and Mining\u00a0\u00bb<\/em><\/a> has been officially accepted as part of\u00a0 IEEE Big Data 2024<\/a> conference.<\/p>\n

December 2023<\/strong>\u00a0 I have defended my habilitation (HDR)<\/strong> thesis entitled \u00ab\u00a0Knowledge discovery from large biological graphs<\/em>\u00ab\u00a0<\/em><\/strong> at the University of Lorraine [Manuscript<\/a>] [Slides<\/a>]<\/p>\n

May 2023<\/strong>\u00a0 Ph.D. Thesis on<\/span> machine learning and graph-based techniques for the prediction of long-term bacterial community structure<\/span><\/em> [More informations<\/a>] [PDF<\/a>]
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April 2023 <\/strong>Our paper \u00ab\u00a0Accuracy and Diversity-Aware Multi-Objective Approach for Random Forest Construction<\/strong>\u00ab\u00a0<\/em> has been accepted for publication in Expert Systems with Applications<\/strong><\/em>, Elsevier, 2023!<\/p>\n

Febrary 2023 <\/strong>Our paper \u00ab\u00a0Molecular-evaluated and explainable drug repurposing for COVID-19 using ensemble knowledge graph embedding<\/em>\u00a0\u00bb <\/strong>has been accepted for publication in Scientific Reports, Nature<\/em> !\u00a0 (IF = 4.99<\/strong>)<\/em>.<\/span><\/p>\n

May 2022 <\/strong>Our paper \u00ab\u00a0Negative Sampling and Rule Mining for Explainable Link Prediction in Knowledge Graphs<\/em>\u00a0\u00bb <\/strong>has been accepted for publication in Knowledge Based Systems<\/em>, Elsevier !\u00a0 (IF = 8.03<\/strong>)<\/em>.<\/span><\/p>\n

April 2022 <\/strong>Our paper \u00ab\u00a0A Distributed and Incremental Algorithm for Large-Scale Graph Clustering <\/em>\u00a0\u00bb <\/strong>has been accepted for publication in Future Generation Computer Systems<\/em>, Elsevier !\u00a0 (IF = 7.18<\/strong>)<\/em>.<\/span><\/p>\n

April 2022 <\/strong>I joined the program committee of the\u00a0Workshop on Computational Biology (WCB)<\/a><\/span> @ ICML 2022<\/a><\/span> <\/strong>Join us for another exciting workshop!
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March 2022<\/strong> Our paper \u00ab\u00a0A semi-supervised graph deep neural networks for automatic protein function annotation\u00a0\u00bb<\/strong><\/em> has been accepted at the 10th International Work-Conference on Bioinformatics and Biomedical Engineering<\/em> (IWBBIO<\/strong>) 2022<\/em>.<\/p>\n

I’m co-organizing the ICML 2021 Workshop on Computational Biology (WCB)<\/strong><\/a><\/span> @ ICML 2021<\/strong><\/a><\/span> Join us for another exciting workshop!<\/p>\n

July 2021\u00a0<\/span><\/cite><\/em><\/strong>Our paper <\/span><\/cite><\/em>\u00ab\u00a0Towards big services: a synergy between service computing and parallel programming\u00a0\u00bb <\/span><\/cite><\/em><\/strong>has been accepted for publication in<\/span><\/cite> <\/cite>Computing, Springer !\u00a0 (IF = 2.22).<\/span><\/strong><\/span><\/cite><\/em><\/p>\n

August 2020 <\/strong>I joined the program committee of the 2020 IEEE International Conference on Big Data (IEEE BigData 2020)<\/a><\/strong>.<\/p>\n

July 2020 <\/strong>Our paper \u00ab\u00a0A comparative study of similarity-based and GNN-based link prediction approaches<\/strong><\/em>\u00a0\u00bb has been accepted at the international Workshop on Graph Embedding and Mining (GEM) in conjunction with ECML-PKDD 2020.
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March 2020<\/strong> Our paper \u00ab\u00a0GrAPFI: Predicting Enzymatic Function of Proteins From Domain Similarity Graphs\u00a0\u00bb<\/strong><\/em> has been accepted for publication in BMC Bioinformatics<\/a> (IF = 2.511<\/strong>)<\/span><\/em>.<\/p>\n

Febrary 2020<\/strong> Our paper \u00ab\u00a0Graph Based Automatic Protein Function Annotation Improved By Semantic Similarity\u00a0\u00bb<\/strong><\/em> has been accepted at the 8th International Work-Conference on Bioinformatics and Biomedical Engineering (IWBBIO<\/strong>) 2020<\/em>.<\/p>\n

September 2019 <\/strong><\/span>Our paper \u00ab\u00a0Multiple instance learning for sequence data with across bag dependencies<\/strong><\/span>\u00ab\u00a0<\/em> has been accepted for publication in International Journal of Machine Learning and Cybernetics<\/a> (IF = 3.844)<\/strong><\/span>!<\/p>\n

September 2019 <\/strong><\/span>Our paper \u00ab\u00a0The CAFA challenge reports improved protein function prediction and new functional annotations for hundreds of genes through experimental screens<\/strong><\/span>\u00ab\u00a0<\/em> has been accepted for publication in Genome Biology<\/a> (IF = 13.58<\/span>)<\/strong>!<\/p>\n

August 2019 <\/strong>Our paper \u00ab\u00a0Application of Artificial Intelligence to Gastroenterology and Hepatology<\/strong>\u00ab\u00a0<\/em> has been accepted for publication in<\/span> Gastroenterology<\/a> (<\/span>IF = 22.68)<\/span><\/strong>!<\/p>\n

May 2019 <\/strong>Our paper \u00ab\u00a0A Structure Based Multiple Instance Learning Approach for Bacterial Ionizing Radiation Resistance Prediction<\/strong>\u00ab\u00a0<\/em> has been accepted at the\u00a023rd International Conference on Knowledge-Based and Intelligent Information & Engineering Systems (KES)<\/strong><\/em> 2019!<\/span><\/p>\n

I\u2019m co-chairing the third edition of the International workshop on\u00a0 Advances in Mining and Managing Large Evolving Graphs (LEG)<\/a><\/strong>\u00a0 in conjunction with ECML-PKDD 2019<\/a><\/strong><\/p>\n

March 2019 <\/strong>Our paper \u00ab\u00a0A Data Sampling and Attribute Selection Strategy for Improving Decision Tree Construction<\/strong>\u00ab\u00a0<\/em> has been accepted for publication in Expert Systems with Applications<\/strong><\/em>, Elsevier, 2019!<\/span><\/p>\n

October 2018 <\/span><\/strong>O<\/span>ur paper \u00ab\u00a0Exploiting Complex Protein Domain Networks for Protein Function Annotation<\/em><\/strong>\u00a0\u00bb has been accepted for publication at Complex Networks 2018<\/a> in Cambridge !<\/span><\/span><\/p>\n

October 2018 <\/span><\/strong>Our paper \u00ab\u00a0<\/span>The Uncertain Cloud: State of the Art and Research Challenges\u00a0\u00bb <\/i><\/strong>has been accepted for publication in the\u00a0International Journal of Approximate Reasoning<\/em>, Elsevier!<\/span><\/span><\/p>\n

August 2018 <\/span><\/strong><\/span>We are editing a special issue of Future Generation Computer Systems (FGCS<\/span>) journal<\/strong>, Elsevier on \u00ab\u00a0Advances in Managing and Mining time varying and highly dynamic graphs at sca<\/strong>le\u00a0\u00bb<\/a>. Please submit your paper here<\/a>!<\/span><\/span><\/p>\n

July 2018<\/span> <\/strong><\/span>Our paper \u00ab\u00a0A Comparative Study on Streaming Frameworks for Big Data<\/strong>\u00a0\u00bb has been accepted for publication at LaDAS@VLDB 2018<\/a> in Rio\u00a0De Janeiro !<\/p>\n

April 2018 <\/strong><\/span>Our paper \u00ab\u00a0An Experimental Survey on Big Data Frameworks<\/em><\/strong>\u00a0\u00bb has been accepted for publication in Future Generation Computer Systems<\/strong><\/em>, Elsevier !<\/p>\n

I\u2019m co-chairing the second edition of the International workshop on\u00a0 Advances in Mining Large-Scale Time Dependent Graphs (TD-LSG)<\/a><\/strong>\u00a0 in conjunction with VLDB 2018<\/a><\/strong><\/span><\/p>\n

I gave a talk on \u00ab\u00a0Dynamic Graph Analysis with BLADYG<\/strong>\u00a0\u00bb at \u00ab\u00a0the GDRI workshop on Web Science<\/strong><\/em>\u00a0\u00bb in Rio De Janeiro.<\/span><\/p>\n

Our paper \u00ab\u00a0An Evolutionary Scheme for Decision Tree Construction<\/strong><\/em><\/a>\u00a0\u00bb received a Honourable Mention in the 2017 Algerian Paper of the Year Award<\/a>.<\/span><\/p>\n

Our paper \u00ab\u00a0An Experimental Survey on Big Data Frameworks<\/em><\/strong>\u00a0\u00bb has been accepted at the 10th Extremely Large Databases Conference (XLDB)<\/strong><\/em> 2017 for a lightning talk.<\/span><\/p>\n

Our paper \u00ab\u00a0A Distributed Framework for Large-Scale Time-Dependent Graph Analysis<\/strong><\/em>\u00a0\u00bb has been accepted at TDLSTG@ECML-PKDD<\/strong> 2017<\/em>.<\/span><\/p>\n

Our paper \u00ab\u00a0BLADYG:<\/strong> A Graph Processing Framework for Large Dynamic Graphs<\/strong><\/em>\u00a0\u00bb has been accepted for publication in Big Data Research<\/strong><\/em>, Elsevier!<\/span><\/p>\n

Our paper \u00ab\u00a0MR-SimLab: Scalable Subgraph Selection with Label Similarity for Big Data<\/strong><\/em>\u00a0\u00bb has been accepted for publication in Information Systems<\/strong><\/em>, Elsevier!<\/span><\/p>\n

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My IEEE MOOC<\/strong> on \u00ab\u00a0Big Data for Smart Cities<\/a>\u00a0\u00bb is out !<\/p>\n